Abstract

Next-generation wireless networks need to support multiclass services with asymmetric bandwidth allocation between uplink and downlink to match the asymmetric traffic load brought by some data services. For the design of call admission control (CAC) policy in such networks, how to decrease the average system cost is a key issue. In this paper, we study the optimal admission policy for minimizing the system cost. We consider the CAC problem as a decision process. By modeling the admission control problem into a Markov decision process (MDP) and analyzing the corresponding value function, we obtain some monotonicity properties of the optimal policy. These properties suggest that the optimal admission control policy for the bandwidth asymmetry wireless networks should have a threshold structure and the threshold specified for a class of calls may change with the system state. Due to the prohibitively high complexity for computing the thresholds in a system with large state-space, we propose a heuristic CAC policy called call-rate-based dynamic threshold (CRDT) policy to approximate the theoretical optimal policy based on the insights we obtain from the modeling and the analytical study on the properties of the optimal policy. The CRDT policy is efficient and can be easily implemented. The numerical results show that the performance of average system cost of the proposed CRDT policy is close to that of the optimal policy from the MDP model and is better than that of some known existing CAC schemes, including those performing well in bandwidth asymmetry wireless networks

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